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arXiv 2409.20133cs.ITmath.IT
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改善零泄漏缓存辅助私有变长编码的可达性

Improving Achievability of Cache-Aided Private Variable-Length Coding with Zero Leakage

Amirreza Zamani, Mikael Skoglund

AI总结:

本文针对缓存辅助私有变长编码问题,提出基于最小熵耦合和贪心熵算法的新可达性方案,在零泄漏约束下改进了现有结果,并利用公共信息概念进一步优化了两种特殊情况的界。

摘要:

研究了一个具有隐私约束的统计缓存辅助压缩问题,其中服务器可以访问一个包含 $N$ 个文件的数据库 $(Y_1,...,Y_N)$,每个文件大小为 $F$ 比特,并通过共享信道连接到 $K$ 个用户,每个用户都有一个大小为 $MF$ 比特的本地缓存。在放置阶段,服务器在不知道用户需求的情况下填充用户的缓存,而交付阶段则在用户向服务器发送需求之后进行。我们假设数据库中的每个文件 $Y_i$ 与私有属性 $X$ 任意相关,并假设对手可以访问共享信道。用户和服务器共享一个密钥 $W$。目标是设计缓存内容和交付消息 $\mathcal{C}$,使得 $\mathcal{C}$ 的平均长度最小化,同时满足:i. 响应 $\mathcal{C}$ 不泄露任何关于 $X$ 的信息,即 $I(X;\mathcal{C})=0$;ii. 用户 $i$ 能够利用共享密钥 $W$、$\mathcal{C}$ 及其本地缓存 $Z_i$ 解码其需求 $Y_{d_i}$。在先前的工作中,我们提出了一种将隐私感知压缩与编码缓存技术相结合的变长编码方案。在本文中,我们提出了一种新的可达性方案,该方案使用最小熵耦合概念和一种基于贪心熵的算法。我们证明所提出的方案改进了先前的结果。此外,针对两种特殊情况,我们利用公共信息概念改进了所获得的界。

英文摘要:

A statistical cache-aided compression problem with a privacy constraint is studied, where a server has access to a database of $N$ files, $(Y_1,...,Y_N)$, each of size $F$ bits and is linked through a shared channel to $K$ users, where each has access to a local cache memory of size $MF$ bits. During the placement phase, the server fills the users' caches without prior knowledge of their demands, while the delivery phase takes place after the users send their demands to the server. We assume that each file in database $Y_i$ is arbitrarily correlated with a private attribute $X$, and an adversary is assumed to have access to the shared channel. The users and the server have access to a shared key $W$. The goal is to design the cache contents and the delivered message $\cal C$ such that the average length of $\mathcal{C}$ is minimized, while satisfying: i. The response $\cal C$ does not reveal any information about $X$, i.e., $I(X;\mathcal{C})=0$; ii. User $i$ can decode its demand, $Y_{d_i}$, by using the shared key $W$, $\cal C$, and its local cache $Z_i$. In a previous work, we have proposed a variable-length coding scheme that combines privacy-aware compression with coded caching techniques. In this paper, we propose a new achievability scheme using minimum entropy coupling concept and a greedy entropy-based algorithm. We show that the proposed scheme improves the previous results. Moreover, considering two special cases we improve the obtained bounds using the common information concept.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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